LTER Instrument Workup 2019
Christina Bonsell
September 11, 2019
Temperature and Salinity Workup
Initial conclusions/questions:
1) Gotta throw out most, if not all EELD1 salinity data. I think these instruments ended up in the mud. Keep the StarOddi temp data from this station.
2) RBR seems more accurate than Star Oddi* (e.g fewer big dips in salinity/conductivity), but still has a scatter of questionable conductivity data. There’s no “cup” to be fouled by sediment, so what is happening?
3) Some of the “non-anomoulus” data I would still throw out. After talking to Tim, this data should be left in but “flagged” in a new column.
Compare instrument types (color points) to YSI data (black points)
EWLD1 and KALD1 could use calibration
Difference in readings between instruments
| Station | mSOvRBR_Temp | mTCMvRBR_Temp | mSOvRBR_Sal |
|---|---|---|---|
| EELD1 | 0.0273978 | 0.1028821 | 7.1917092 |
| EELD2 | NaN | NaN | NaN |
| EWLD1 | NaN | NaN | NaN |
| EWLD2 | -0.0498599 | 0.0205760 | -6.7605868 |
| JALD1 | NaN | NaN | NaN |
| JALD2 | -0.0337953 | -0.0147414 | -0.8162601 |
| KALD1 | NaN | NaN | NaN |
| KALD2 | -0.0292570 | 0.0584142 | -4.1743281 |
| Station | DT | Temp_YSI | Temp_SO | Temp_RBR | Temp_TCM |
|---|---|---|---|---|---|
| KALD1 | 2019-04-28 12:00:00 | -1.8 | -1.74 | NA | -1.7069 |
| KALD1 | 2019-08-08 10:00:00 | 9.1 | 9.10 | NA | 9.7457 |
| JALD2 | 2019-04-27 13:00:00 | -1.7 | -1.50 | -1.4511464 | -1.4039 |
| JALD2 | 2019-06-21 11:00:00 | 0.9 | -0.08 | -0.0574337 | -0.1048 |
| JALD2 | 2019-08-09 11:00:00 | 5.9 | 6.01 | 7.5277501 | 6.4134 |
| EELD2 | 2019-07-31 18:00:00 | 7.7 | 8.00 | NA | 8.0202 |
| EELD1 | 2019-04-16 12:00:00 | -1.8 | -1.76 | -1.6958582 | -1.8956 |
| EELD1 | 2019-07-31 20:00:00 | 9.1 | 7.37 | 6.8960178 | 7.8434 |
| KALD2 | 2019-04-25 22:00:00 | -1.6 | -1.88 | -1.8313716 | -1.5500 |
| KALD2 | 2019-06-21 15:00:00 | -0.1 | -0.05 | -0.2430046 | 0.0767 |
| KALD2 | 2019-08-08 00:00:00 | 9.1 | 9.39 | 9.2768836 | NA |
| JALD1 | 2019-08-09 10:00:00 | 7.5 | 7.41 | NA | 7.4373 |
| EWLD2 | 2018-08-11 17:00:00 | 5.4 | 5.47 | NA | 5.4700 |
| EWLD2 | 2019-04-15 13:00:00 | -1.8 | -1.76 | -1.7381441 | -1.7501 |
| EWLD2 | 2019-08-05 15:00:00 | 9.6 | 9.54 | 9.7726169 | 9.7214 |
| EWLD1 | 2018-08-11 18:00:00 | 6.8 | 5.96 | NA | 5.9905 |
| EWLD1 | 2019-04-13 19:00:00 | -2.0 | -1.81 | NA | -1.8506 |
| EWLD1 | 2019-06-23 18:00:00 | -0.3 | -0.69 | NA | NA |
| EWLD1 | 2019-06-24 15:00:00 | -0.2 | -0.44 | NA | NA |
| EWLD1 | 2019-08-05 16:00:00 | 9.9 | 10.01 | NA | NA |
| Station | DT | Sal_YSI | Sal_SO | Sal_RBR |
|---|---|---|---|---|
| KALD1 | 2019-04-28 12:00:00 | 39.33 | 36.17 | NA |
| KALD1 | 2019-08-08 10:00:00 | 25.93 | 23.54 | NA |
| JALD2 | 2019-04-27 13:00:00 | 38.81 | 42.18 | 42.634513 |
| JALD2 | 2019-06-21 11:00:00 | 33.35 | 38.12 | 39.908007 |
| JALD2 | 2019-08-09 11:00:00 | 29.87 | 23.38 | 26.290954 |
| EELD2 | 2019-07-31 18:00:00 | 25.89 | 25.85 | NA |
| EELD1 | 2019-04-16 12:00:00 | 35.34 | 18.48 | 9.174136 |
| EELD1 | 2019-07-31 20:00:00 | 24.55 | 14.94 | 9.449980 |
| KALD2 | 2019-04-25 22:00:00 | 39.70 | 36.25 | 39.090341 |
| KALD2 | 2019-06-21 15:00:00 | 39.03 | 35.93 | 38.840524 |
| KALD2 | 2019-08-08 00:00:00 | 25.98 | 23.68 | 21.540167 |
| JALD1 | 2019-08-09 10:00:00 | 25.32 | 24.31 | NA |
| EWLD2 | 2018-08-11 17:00:00 | 29.39 | 26.72 | NA |
| EWLD2 | 2019-04-15 13:00:00 | 35.33 | 25.35 | 31.878105 |
| EWLD2 | 2019-08-05 15:00:00 | 29.70 | 17.49 | 28.676686 |
| EWLD1 | 2018-08-11 18:00:00 | 27.31 | 22.13 | NA |
| EWLD1 | 2019-04-13 19:00:00 | 34.60 | 32.85 | NA |
| EWLD1 | 2019-06-23 18:00:00 | 10.54 | 31.98 | NA |
| EWLD1 | 2019-06-24 15:00:00 | 6.67 | 31.97 | NA |
| EWLD1 | 2019-08-05 16:00:00 | 30.31 | 24.67 | NA |
calibrate EWLD1 and KALD1 using YSI data
T vs S
What to remove (“anom” data is below TS line givin instrument precision)
## [1] "SO error: T=0.1, Cond=1.5 mS/cm, RBR error: T=0.002, Cond=0.01 mS/cm"
#Choose datasets ##color=StarOddi, black=RBR ##use KALD1 calibrated for Temp and Cond, EWLD1 calibrated for Cond 
Next step = Flagging data
Values below freezing line (with error) are flagged “INV” for Invalid
Values that are outliers, or appear to be instrument malfunction (as determined by a trained human) are flagged “QM” for Questionable Measurement
